1 files changed, 0 insertions, 96 deletions
diff --git a/test/de/lmu/ifi/dbs/elki/algorithm/clustering/correlation/TestCASHResults.java b/test/de/lmu/ifi/dbs/elki/algorithm/clustering/correlation/TestCASHResults.java
deleted file mode 100644
index 62791b68..00000000
--- a/test/de/lmu/ifi/dbs/elki/algorithm/clustering/correlation/TestCASHResults.java
+++ /dev/null
@@ -1,96 +0,0 @@
-package de.lmu.ifi.dbs.elki.algorithm.clustering.correlation;
-
-/*
- This file is part of ELKI:
- Environment for Developing KDD-Applications Supported by Index-Structures
-
- Copyright (C) 2012
- Ludwig-Maximilians-Universität München
- Lehr- und Forschungseinheit für Datenbanksysteme
- ELKI Development Team
-
- This program is free software: you can redistribute it and/or modify
- it under the terms of the GNU Affero General Public License as published by
- the Free Software Foundation, either version 3 of the License, or
- (at your option) any later version.
-
- This program is distributed in the hope that it will be useful,
- but WITHOUT ANY WARRANTY; without even the implied warranty of
- MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
- GNU Affero General Public License for more details.
-
- You should have received a copy of the GNU Affero General Public License
- along with this program.  If not, see <http://www.gnu.org/licenses/>.
- */
-
-import org.junit.Test;
-
-import de.lmu.ifi.dbs.elki.JUnit4Test;
-import de.lmu.ifi.dbs.elki.algorithm.AbstractSimpleAlgorithmTest;
-import de.lmu.ifi.dbs.elki.data.Clustering;
-import de.lmu.ifi.dbs.elki.data.DoubleVector;
-import de.lmu.ifi.dbs.elki.data.model.Model;
-import de.lmu.ifi.dbs.elki.database.Database;
-import de.lmu.ifi.dbs.elki.utilities.ClassGenericsUtil;
-import de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.ListParameterization;
-
-/**
- * Perform a full CASH run, and compare the result with a clustering derived
- * from the data set labels. This test ensures that CASH performance doesn't
- * unexpectedly drop on this data set (and also ensures that the algorithms
- * work, as a side effect).
- * 
- * @author Erich Schubert
- * @author Katharina Rausch
- */
-public class TestCASHResults extends AbstractSimpleAlgorithmTest implements JUnit4Test {
-  /**
-   * Run CASH with fixed parameters and compare the result to a golden standard.
-   */
-  @Test
-  public void testCASHResults() {
-    // Input
-    Database db = makeSimpleDatabase(UNITTEST + "hierarchical-3d2d1d.csv", 600, new ListParameterization(), null);
-
-    // CASH parameters
-    ListParameterization params = new ListParameterization();
-    params.addParameter(CASH.JITTER_ID, 0.7);
-    params.addParameter(CASH.MINPTS_ID, 50);
-    params.addParameter(CASH.MAXLEVEL_ID, 25);
-    params.addFlag(CASH.ADJUST_ID);
-
-    // setup algorithm
-    CASH<DoubleVector> cash = ClassGenericsUtil.parameterizeOrAbort(CASH.class, params);
-    testParameterizationOk(params);
-
-    // run CASH on database
-    Clustering<Model> result = cash.run(db);
-
-    testFMeasure(db, result, 0.490551); // with hierarchical pairs: 0.64102
-    testClusterSizes(result, new int[] { 37, 71, 76, 442 });
-  }
-
-  /**
-   * Run CASH with fixed parameters and compare the result to a golden standard.
-   */
-  @Test
-  public void testCASHEmbedded() {
-    // CASH input
-    Database db = makeSimpleDatabase(UNITTEST + "correlation-embedded-2-4d.ascii", 600, new ListParameterization(), null);
-
-    // CASH parameters
-    ListParameterization params = new ListParameterization();
-    params.addParameter(CASH.JITTER_ID, 0.7);
-    params.addParameter(CASH.MINPTS_ID, 160);
-    params.addParameter(CASH.MAXLEVEL_ID, 40);
-
-    // setup algorithm
-    CASH<DoubleVector> cash = ClassGenericsUtil.parameterizeOrAbort(CASH.class, params);
-    testParameterizationOk(params);
-
-    // run CASH on database
-    Clustering<Model> result = cash.run(db);
-    testFMeasure(db, result, 0.443246);
-    testClusterSizes(result, new int[] { 169, 196, 235 });
-  }
-}
-\ No newline at end of file